




"""simple docstring"""




from __future__ import annotations

import random
import unittest

from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
			import tensorflow as tf

			from transformers import (
			    TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
			    TFTransfoXLForSequenceClassification,
			    TFTransfoXLLMHeadModel,
			    TFTransfoXLModel,
			)

class   UpperCAmelCase_    :
		def __init__(						self				,						UpperCamelCase_				,						)						->       List[Any]:
					__lowercase			:  List[str]								=       parent
					__lowercase			:  Tuple								=       13
					__lowercase			:  int								=       7
					__lowercase			:  str								=       30
					__lowercase			:  int								=       self.seq_length + self.mem_len
					__lowercase			:  Optional[Any]								=       15
					__lowercase			:  Optional[int]								=       True
					__lowercase			:  Union[str, Any]								=       True
					__lowercase			:  Optional[int]								=       99
					__lowercase			:  int								=       [10, 50, 80]
					__lowercase			:  List[str]								=       32
					__lowercase			:  str								=       32
					__lowercase			:  Optional[Any]								=       4
					__lowercase			:  Any								=       8
					__lowercase			:  Dict								=       1_28
					__lowercase			:  Optional[int]								=       2
					__lowercase			:  Any								=       2
					__lowercase			:  Dict								=       None
					__lowercase			:  Optional[Any]								=       1
					__lowercase			:  Optional[int]								=       0
					__lowercase			:  Optional[Any]								=       3
					__lowercase			:  int								=       self.vocab_size - 1
					__lowercase			:  List[Any]								=       0.0_1
		def 	_lowerCamelCase							(						self       )						->       Dict:
					__lowercase			:  Union[str, Any]								=       ids_tensor([self.batch_size, self.seq_length]				,						self.vocab_size       )
					__lowercase			:  Dict								=       ids_tensor([self.batch_size, self.seq_length]				,						self.vocab_size       )

					__lowercase			:  Optional[int]								=       None
					if self.use_labels:
								__lowercase			:  List[Any]								=       ids_tensor([self.batch_size, self.seq_length]				,						self.vocab_size       )

					__lowercase			:  Tuple								=       TransfoXLConfig(
					    vocab_size=self.vocab_size				,						mem_len=self.mem_len				,						clamp_len=self.clamp_len				,						cutoffs=self.cutoffs				,						d_model=self.hidden_size				,						d_embed=self.d_embed				,						n_head=self.num_attention_heads				,						d_head=self.d_head				,						d_inner=self.d_inner				,						div_val=self.div_val				,						n_layer=self.num_hidden_layers				,						eos_token_id=self.eos_token_id				,						pad_token_id=self.vocab_size - 1				,						init_range=self.init_range				,						num_labels=self.num_labels				,						)

					return (config, input_ids_a, input_ids_a, lm_labels)
		def 	_lowerCamelCase							(						self       )						->       int:
					random.seed(self.seed       )
					tf.random.set_seed(self.seed       )
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_       )						->       Tuple:
					__lowercase			:  Dict								=       TFTransfoXLModel(UpperCamelCase_       )

					__lowercase			,__lowercase			:  int								=       model(UpperCamelCase_       ).to_tuple()

					__lowercase			:  str								=       {'''input_ids''': input_ids_a, '''mems''': mems_a}

					__lowercase			,__lowercase			:  int								=       model(UpperCamelCase_       ).to_tuple()

					self.parent.assertEqual(hidden_states_a.shape				,						(self.batch_size, self.seq_length, self.hidden_size)       )
					self.parent.assertEqual(hidden_states_a.shape				,						(self.batch_size, self.seq_length, self.hidden_size)       )
					self.parent.assertListEqual(
					    [mem.shape for mem in mems_a]				,						[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers				,						)
					self.parent.assertListEqual(
					    [mem.shape for mem in mems_a]				,						[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers				,						)
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_       )						->       List[str]:
					__lowercase			:  List[str]								=       TFTransfoXLLMHeadModel(UpperCamelCase_       )

					__lowercase			,__lowercase			:  Optional[int]								=       model(UpperCamelCase_       ).to_tuple()

					__lowercase			:  Dict								=       {'''input_ids''': input_ids_a, '''labels''': lm_labels}
					__lowercase			,__lowercase			:  int								=       model(UpperCamelCase_       ).to_tuple()

					__lowercase			,__lowercase			:  Optional[int]								=       model([input_ids_a, mems_a]       ).to_tuple()

					__lowercase			:  Optional[Any]								=       {'''input_ids''': input_ids_a, '''mems''': mems_a, '''labels''': lm_labels}

					__lowercase			,__lowercase			:  Tuple								=       model(UpperCamelCase_       ).to_tuple()

					self.parent.assertEqual(lm_logits_a.shape				,						(self.batch_size, self.seq_length, self.vocab_size)       )
					self.parent.assertListEqual(
					    [mem.shape for mem in mems_a]				,						[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers				,						)

					self.parent.assertEqual(lm_logits_a.shape				,						(self.batch_size, self.seq_length, self.vocab_size)       )
					self.parent.assertListEqual(
					    [mem.shape for mem in mems_a]				,						[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers				,						)
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_       )						->       Optional[Any]:
					__lowercase			:  Tuple								=       TFTransfoXLForSequenceClassification(UpperCamelCase_       )
					__lowercase			:  Optional[int]								=       model(UpperCamelCase_       )
					self.parent.assertEqual(result.logits.shape				,						(self.batch_size, self.num_labels)       )
		def 	_lowerCamelCase							(						self       )						->       Union[str, Any]:
					__lowercase			:  List[str]								=       self.prepare_config_and_inputs()
					((__lowercase)			,(__lowercase)			,(__lowercase)			,(__lowercase))			:  int								=       config_and_inputs
					__lowercase			:  Tuple								=       {'''input_ids''': input_ids_a}
					return config, inputs_dict


@require_tf
class   UpperCAmelCase_    (			snake_case   ,					snake_case   ,					unittest.TestCase		):
		UpperCamelCase							=(
		    (TFTransfoXLModel, TFTransfoXLLMHeadModel, TFTransfoXLForSequenceClassification) if is_tf_available() else ()
		)
		UpperCamelCase							=() if is_tf_available() else ()
		UpperCamelCase							=(
		    {
		        "feature-extraction": TFTransfoXLModel,
		        "text-classification": TFTransfoXLForSequenceClassification,
		        "text-generation": TFTransfoXLLMHeadModel,
		        "zero-shot": TFTransfoXLForSequenceClassification,
		    }
		    if is_tf_available()
		    else {}
		)
		# TODO: add this test when TFTransfoXLLMHead has a linear output layer implemented
		UpperCamelCase							=False
		UpperCamelCase							=False
		UpperCamelCase							=False
		UpperCamelCase							=False
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_				,						UpperCamelCase_       )						->       Dict:
					if pipeline_test_casse_name == "TextGenerationPipelineTests":
								# Get `ValueError: AttributeError: 'NoneType' object has no attribute 'new_ones'` or `AssertionError`.
								# `TransfoXLConfig` was never used in pipeline tests: cannot create a simple
								# tokenizer.
								return True

					return False
		def 	_lowerCamelCase							(						self       )						->       Optional[Any]:
					__lowercase			:  Optional[Any]								=       TFTransfoXLModelTester(self       )
					__lowercase			:  List[str]								=       ConfigTester(self				,						config_class=UpperCamelCase_				,						d_embed=37       )
		def 	_lowerCamelCase							(						self       )						->       List[Any]:
					self.config_tester.run_common_tests()
		def 	_lowerCamelCase							(						self       )						->       List[Any]:
					self.model_tester.set_seed()
					__lowercase			:  List[str]								=       self.model_tester.prepare_config_and_inputs()
					self.model_tester.create_and_check_transfo_xl_model(*UpperCamelCase_       )
		def 	_lowerCamelCase							(						self       )						->       List[str]:
					self.model_tester.set_seed()
					__lowercase			:  Union[str, Any]								=       self.model_tester.prepare_config_and_inputs()
					self.model_tester.create_and_check_transfo_xl_lm_head(*UpperCamelCase_       )
		def 	_lowerCamelCase							(						self       )						->       str:
					__lowercase			:  Tuple								=       self.model_tester.prepare_config_and_inputs()
					self.model_tester.create_and_check_transfo_xl_for_sequence_classification(*UpperCamelCase_       )
		def 	_lowerCamelCase							(						self       )						->       List[str]:
					__lowercase			,__lowercase			:  Optional[int]								=       self.model_tester.prepare_config_and_inputs_for_common()
					__lowercase			:  Any								=       [TFTransfoXLForSequenceClassification]

					for model_class in self.all_model_classes:
								__lowercase			:  List[Any]								=       model_class(UpperCamelCase_       )
								assert isinstance(model.get_input_embeddings()				,						tf.keras.layers.Layer       )
								if model_class in list_other_models_with_output_ebd:
											__lowercase			:  int								=       model.get_output_embeddings()
											assert isinstance(UpperCamelCase_				,						tf.keras.layers.Layer       )
											__lowercase			:  int								=       model.get_bias()
											assert name is None
								else:
											__lowercase			:  Optional[int]								=       model.get_output_embeddings()
											assert x is None
											__lowercase			:  Any								=       model.get_bias()
											assert name is None
		def 	_lowerCamelCase							(						self       )						->       Optional[int]:
					# TODO JP: Make TransfoXL XLA compliant
					pass
		@slow
		def 	_lowerCamelCase							(						self       )						->       Union[str, Any]:
					for model_name in TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
								__lowercase			:  int								=       TFTransfoXLModel.from_pretrained(UpperCamelCase_       )
								self.assertIsNotNone(UpperCamelCase_       )
		@unittest.skip(reason='''This model doesn\'t play well with fit() due to not returning a single loss.'''       )
		def 	_lowerCamelCase							(						self       )						->       List[str]:
					pass


@require_tf
class   UpperCAmelCase_    (			unittest.TestCase		):
		@unittest.skip('''Skip test until #12651 is resolved.'''       )
		@slow
		def 	_lowerCamelCase							(						self       )						->       List[Any]:
					__lowercase			:  int								=       TFTransfoXLLMHeadModel.from_pretrained('''transfo-xl-wt103'''       )
					# fmt: off
					__lowercase			:  Tuple								=       tf.convert_to_tensor([[33,12_97,2,1,10_09,4,11_09,1_17_39,47_62,3_58,5,25,2_45,22,17_06,17,2_00_98,5,32_15,21,37,11_10,3,13,10_41,4,24,6_03,4_90,2,7_14_77,2_00_98,10_44_47,2,2_09_61,1,26_04,4,1,3_29,3,62_24,8_31,1_60_02,2,8,6_03,7_89_67,2_95_46,23,8_03,20,25,4_16,5,8,2_32,4,2_77,6,18_55,46_01,3,2_95_46,54,8,36_09,5,5_72_11,49,4,1,2_77,18,8,17_55,1_56_91,3,3_41,25,4_16,6_93,4_25_73,71,17,4_01,94,31,1_79_19,2,2_95_46,78_73,18,1,4_35,23,1_10_11,7_55,5,51_67,3,79_83,98,84,2,2_95_46,32_67,8,36_09,4,1,48_65,10_75,2,60_87,71,6,3_46,8,58_54,3,2_95_46,8_24,14_00,18_68,2,19,1_60,2,3_11,8,54_96,2,2_09_20,17,25,1_50_97,3,24,24,0]]				,						dtype=tf.intaa       )  # noqa: E231
					# fmt: on
					#  In 1991 , the remains of Russian Tsar Nicholas II and his family
					#  ( except for Alexei and Maria ) are discovered .
					#  The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
					#  remainder of the story . 1883 Western Siberia ,
					#  a young Grigori Rasputin is asked by his father and a group of men to perform magic .
					#  Rasputin has a vision and denounces one of the men as a horse thief . Although his
					#  father initially slaps him for making such an accusation , Rasputin watches as the
					#  man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
					#  the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
					#  with people , even a bishop , begging for his blessing . <eod> </s> <eos>

					# fmt: off
					__lowercase			:  Union[str, Any]								=       [33,12_97,2,1,10_09,4,11_09,1_17_39,47_62,3_58,5,25,2_45,22,17_06,17,2_00_98,5,32_15,21,37,11_10,3,13,10_41,4,24,6_03,4_90,2,7_14_77,2_00_98,10_44_47,2,2_09_61,1,26_04,4,1,3_29,3,62_24,8_31,1_60_02,2,8,6_03,7_89_67,2_95_46,23,8_03,20,25,4_16,5,8,2_32,4,2_77,6,18_55,46_01,3,2_95_46,54,8,36_09,5,5_72_11,49,4,1,2_77,18,8,17_55,1_56_91,3,3_41,25,4_16,6_93,4_25_73,71,17,4_01,94,31,1_79_19,2,2_95_46,78_73,18,1,4_35,23,1_10_11,7_55,5,51_67,3,79_83,98,84,2,2_95_46,32_67,8,36_09,4,1,48_65,10_75,2,60_87,71,6,3_46,8,58_54,3,2_95_46,8_24,14_00,18_68,2,19,1_60,2,3_11,8,54_96,2,2_09_20,17,25,1_50_97,3,24,24,0,33,1,18_57,2,1,10_09,4,11_09,1_17_39,47_62,3_58,5,25,2_45,28,11_10,3,13,10_41,4,24,6_03,4_90,2,7_14_77,2_00_98,10_44_47,2,2_09_61,1,26_04,4,1,3_29,3,0]  # noqa: E231
					# fmt: on
					#  In 1991, the remains of Russian Tsar Nicholas II and his family (
					#  except for Alexei and Maria ) are discovered. The voice of young son,
					#  Tsarevich Alexei Nikolaevich, narrates the remainder of the story.
					#  1883 Western Siberia, a young Grigori Rasputin is asked by his father
					#  and a group of men to perform magic. Rasputin has a vision and
					#  denounces one of the men as a horse thief. Although his father initially
					#  slaps him for making such an accusation, Rasputin watches as the man
					#  is chased outside and beaten. Twenty years later, Rasputin sees a vision
					#  of the Virgin Mary, prompting him to become a priest.
					#  Rasputin quickly becomes famous, with people, even a bishop, begging for
					#  his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
					# Nicholas II and his family were discovered. The voice of <unk> young son,
					# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>

					__lowercase			:  List[str]								=       model.generate(UpperCamelCase_				,						max_length=2_00				,						do_sample=UpperCamelCase_       )
					self.assertListEqual(output_ids[0].numpy().tolist()				,						UpperCamelCase_       )








'''simple docstring'''






import numpy as np
def  lowerCamelCase__			(		_A							):
  return 1 / (1 + np.exp(-vector							))
def  lowerCamelCase__			(		_A							):
  return vector * sigmoid(1.702 * vector							)


if __name__ == "__main__":
     import doctest

     doctest.testmod()